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Data sharing creates potential cost savings, supports data aggregation, and facilitates reproducibility to ensure quality research; however, data from heterogeneous systems require retrospective harmonization. This is a major hurdle for researchers who seek to leverage existing data. Efforts focused on strategies for data interoperability largely center around the use of standards but ignore the problems of competing standards and the value of existing data. Interoperability remains reliant on retrospective harmonization. Approaches to reduce this burden are needed.

Call for Data Standardization: Lessons Learned and Recommendations in an Imaging Study